Tzu-Mao Li
I am joining the CSE department of UCSD as an assistant professor in July 2021. Please consider applying for the graduate program if you are interested in working on things listed below.

I am a postdoctoral researcher at MIT CSAIL, working with Jonathan Ragan-Kelley. I explore the connections between visual computing algorithms and modern data-driven methods and develop programming systems for facilitating the exploration. I did a 6-month postdoc with Jonathan Ragan-Kelley at UC Berkeley, and did my Ph.D. in the computer graphics group at MIT CSAIL, advised by Frédo Durand. I received my B.S. and M.S. degrees in computer science and information engineering from National Taiwan University in 2011 and 2013, respectively, where I worked with Yung-Yu Chuang at the Communication and Multimedia Lab.


Code, slides, video, papers are in the project pages.

DiffTaichi: Differentiable Programming for Physical Simulation
Yuanming Hu, Luke Anderson, Tzu-Mao Li, Qi Sun, Nathan Carr, Jonathan Ragan-Kelley, Fredo Durand
International Conference on Learning Representation (ICLR) 2020, to appear
automatic differentiated Taichi and applications in model-based reinforcement learning
Taichi: A Language for High-Performance Computation on Spatially Sparse Data Structures
Yuanming Hu, Tzu-Mao Li, Luke Anderson, Jonathan Ragan-Kelley, Frédo Durand
ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2019)
a data-oriented compiler that decouples hierarchical sparse data structures design from computation
Learning to Optimize Halide with Tree Search and Random Programs
Andrew Adams, Karima Ma, Luke Anderson, Riyadh Baghdadi, Tzu-Mao Li, Michaël Gharbi, Benoit Steiner, Steven Johnson, Kayvon Fatahalian, Frédo Durand, Jonathan Ragan-Kelley
ACM Transactions on Graphics (Proceedings of SIGGRAPH 2019)
first Halide autoscheduler that produces faster code comparing to human experts on average
Sample-based Monte Carlo Denoising using a Kernel-Splatting Network
Michaël Gharbi, Tzu-Mao Li, Miika Aittala, Jaakko Lehtinen, Frédo Durand
ACM Transactions on Graphics (Proceedings of SIGGRAPH 2019).
permutation invariant mapping from Monte Carlo samples to an image through splatting
Differentiable Visual Computing [slides (Keynote)] [slides (Powerpoint)]
Tzu-Mao Li
MIT PhD Dissertation
ACM SIGGRAPH 2020 Outstanding Doctoral Dissertation Award (announcement)
a coherent view of my PhD research, with some new discussions regarding previous papers, and some background reviews
Inverse Path Tracing for Joint Material and Lighting Estimation
Dejan Azinović, Tzu-Mao Li, Anton Kaplanyan, Matthias Nießner
Conference on Computer Vision and Pattern Recognition (CVPR), 2019 (oral presentation)
applying differentiable rendering for material and lighting reconstruction
Differentiable Monte Carlo Ray Tracing through Edge Sampling
Tzu-Mao Li, Miika Aittala, Frédo Durand, Jaakko Lehtinen
ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2018)
computing gradients of the light transport equation through an explicit sampling of Dirac delta functions on triangle edges
Differentiable Programming for Image Processing and Deep Learning in Halide
Tzu-Mao Li, Michaël Gharbi, Andrew Adams, Frédo Durand, Jonathan Ragan-Kelley
ACM Transactions on Graphics (Proceedings of SIGGRAPH 2018)
Halide meets automatic differentiation.
Aether: An Embedded Domain Specific Sampling Language for Monte Carlo Rendering
Luke Anderson, Tzu-Mao Li, Jaakko Lehtinen, Frédo Durand
ACM Transactions on Graphics (Proceedings of SIGGRAPH 2017)
a programming language for Monte Carlo rendering that automatically computes the probability density of a light path sample
Anisotropic Gaussian Mutations for Metropolis Light Transport through Hessian-Hamiltonian Dynamics
Tzu-Mao Li, Jaakko Lehtinen, Ravi Ramamoorthi, Wenzel Jakob, Frédo Durand
ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2015)
a variant of Metropolis light transport algorithm that makes use of automatically differentiated Hessian matrix of light path contribution
Dual-Matrix Sampling for Scalable Translucent Material Rendering
Yu-Ting Wu, Tzu-Mao Li, Yu-Hsun Lin, and Yung-Yu Chuang
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2015
subsurface scattering with many-lights using matrix sampling
SURE-based Optimization for Adaptive Sampling and Reconstruction
Tzu-Mao Li, Yu-Ting Wu, Yung-Yu Chuang
ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2012)
Stein's unbiased risk estimator for sampling and denoising in Monte Carlo rendering

Word cloud

Some keywords extracted from the publications above. They might give you some sense of my research.


A differentiable Monte Carlo ray tracer with PyTorch and Tensorflow interfaces.
Graphics bibtex
A mega bibtex file containing many graphics-related literatures.
Joint Stein’s Unbiased Risk Estimation for Adaptive Sampling and Reconstruction
A short note on a generalized formulation of our SURE-based rendering method.
My prototypical renderer.
Gradient-Domain Path Tracing in ~450 lines.